[ FreeCourseWeb.com ] AWS Certified Machine Learning-Specialty (ML-S)
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Video: .MP4, 1280x720 30 fps | Audio: AAC, 44.1 kHz, 2ch | Duration: 7h
Genre: eLearning | Language: English | Size: 9.7 GB
This course covers the essentials of Machine Learning on AWS and prepares a candidate to sit for the AWS Machine Learning-Specialty (ML-S) Certification exam. Four main categories are covered: Data Engineering, EDA (Exploratory Data Analysis), Modeling, and Operations. Description This 7+ hour Complete Video Course is fully geared toward the AWS Machine Learning-Specialty (ML-S) Certification exam. The course offers a modular lesson and sublesson approach, with a mix of screencasting and headhsot treatment.
Data Engineering instruction covers the ingestion, cleaning, and maintenance of data on AWS.
Exploratory Data Analysis covers topics including data visualization, descriptive statistics, and dimension reduction and includes information on relevant AWS services.
Machine Learning Modeling covers topics including feature engineering, performance metrics, overfitting, and algorithm selection.
Operations covers deploying models, A/B testing, using AI services versus training your own model, and proper cost utilization.
The supporting code for this LiveLesson is located at http://www.informit.com/store/aws-certified-machine-learning-specialty-ml-s-complete-9780135556511.
About the Instructor
Noah Gift is a lecturer and consultant at both the UC Davis Graduate School of Management MSBA program and the Graduate Data Science program, MSDS, at Northwestern. He teaches and designs graduate machine learning, AI, data science courses, and consulting on machine learning and cloud architecture for students and faculty. These responsibilities include leading a multi-cloud certification initiative for students. Noah is a Python Software Foundation Fellow, AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect, AWS Academy accredited instructor, Google Certified Professional Cloud Architect, and Microsoft MTA on Python. Noah has published close to 100 technical publications including two books on subjects ranging from cloud machine learning to DevOps.
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